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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Deep Learning on High-Throughput Transcriptomics to Predict Drug-Induced Liver Injury
|
|---|---|
| Published in |
Frontiers in Bioengineering and Biotechnology, November 2020
|
| DOI | 10.3389/fbioe.2020.562677 |
| Pubmed ID | |
| Authors |
Ting Li, Weida Tong, Ruth Roberts, Zhichao Liu, Shraddha Thakkar |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 13% |
| Canada | 1 | 7% |
| Unknown | 12 | 80% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 9 | 60% |
| Scientists | 5 | 33% |
| Science communicators (journalists, bloggers, editors) | 1 | 7% |
Mendeley readers
The data shown below were compiled from readership statistics for 40 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 40 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 9 | 23% |
| Researcher | 8 | 20% |
| Student > Master | 5 | 13% |
| Student > Bachelor | 3 | 8% |
| Librarian | 1 | 3% |
| Other | 3 | 8% |
| Unknown | 11 | 28% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 8 | 20% |
| Computer Science | 4 | 10% |
| Chemistry | 3 | 8% |
| Medicine and Dentistry | 3 | 8% |
| Agricultural and Biological Sciences | 2 | 5% |
| Other | 7 | 18% |
| Unknown | 13 | 33% |
Attention Score in Context
This research output has an Altmetric Attention Score of 8. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 17 December 2020.
All research outputs
#4,587,281
of 24,505,736 outputs
Outputs from Frontiers in Bioengineering and Biotechnology
#679
of 7,903 outputs
Outputs of similar age
#118,020
of 519,065 outputs
Outputs of similar age from Frontiers in Bioengineering and Biotechnology
#45
of 298 outputs
Altmetric has tracked 24,505,736 research outputs across all sources so far. Compared to these this one has done well and is in the 81st percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,903 research outputs from this source. They receive a mean Attention Score of 3.6. This one has done particularly well, scoring higher than 91% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 519,065 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 77% of its contemporaries.
We're also able to compare this research output to 298 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 85% of its contemporaries.